To identify the sites with elevated metal concentrations and factors impacting the concentrations, we studied 128 observations on heavy metals collected from the four inch deep sediments in Louisiana lakes and rivers. Use of Fe as a normalizing factor to interpret the site of metal enrichment was justified based on its high correlation with other heavy metals. The regression coefficients of metal/Fe came out to be significant for all the metals in both level and log versions. For the metals, where prediction exceeded upper 95% confidence interval, we mapped the site with factors such as number of industries located within a five mile radius, distance to major roadways, and road length within one mile. GIS maps were developed for major sites where the selected metals (Cd, Cr, Cu, Ni, Pb, Zn) exceeded 95% upper confidence interval. In addition to that, multiple regression models were developed. The dependent variable is regressed to land use (six categories), sediment texture, pH, population density, income, industry concentration, road length within one mile distance, and organic matter content with the objective of pointing out the variables significant in causing the elevated metal concentration. Though in many of the metal enriched areas texture of the sediment was fine grained silt clay loam, the relationship did not come out to be significant in regression models. Cu concentration is negatively significant with water as a landuse type. Cd, Cr, Cu, Ni, and Zn are significantly related to number of industries. Relationship of Cr and Ni to organic matter and per capita income is significant. Results confirmed the many findings in literature such as the positive correlation of metal concentrations to organic matter, sediment texture, industries and particular landuse type. The findings from this study shed light on interpretation of heavy metal enrichment sites and various anthropogenic as well as natural factors impacting the metal concentration in sediments.